Optimization Design Of The Robot Maze Search Flood Algorithm

During the "13th Five-Year Plan" period,the intelligent robot industry will play an increasingly important role in the industrial transformation,In the industrial manufacturing,medical applications,outer space exploration,the exploration of dangerous areas,family cleaning,service industries and other fields will also be promising.As a miniature in the "robot tide",the development prospects of the labyrinth search robot will be unlimited.Search algorithm as a maze search robot "soul",like the human brain,directly determines the direction of movement of the robot and the route,which is of great significance to improve the efficiency of robot search.The current flood algorithm because of its own algorithm features,of course,there are other algorithms can not match the advantages,such as the optimal path of the solution.However,the flood algorithm also has the problem of randomization algorithm,that is,when the "flood" random spread will be probably spread to the periphery of some "dead zone",and the flood algorithm has the problem of repeated search,thereby reducing the search efficiency.Therefore,it is of great significance and value to study the maze search robot with improved flood algorithm,which is of great significance and value to improve the performance of the game and shorten the gap with foreign players,and it has important basic theoretical significance and application value for the search of intelligent robot,the disaster relief in the disaster area,the deep seabed search,the exploration of unknown planet and the development of artificial intelligence.The paper first briefly describes the background and significance of this study,and the domestic and foreign research status comparison,obtained the domestic search algorithm and foreign algorithms still have a certain gap.Then,the principle of breadthfirst algorithm,depth-first algorithm,flood search algorithm,left-hand algorithm,righthand algorithm algorithm and optimization of flood algorithm are discussed in detail,and the above algorithm is analyzed in detail in the principle and optimization method.Then the simulation platform of the search algorithm is constructed,which realizes the function of random generation of maze,shortest path display,step number display,time display,search area display and middle quantity crawling.In the realization of the random generation of the maze,found that the common random maze generation ideas can not generate the maze to meet the requirements,need to grasp the second step and n-1 step position and maze state,and to amend,in order to generate a maze to meet the requirements.It is concluded that the optimization algorithm is more efficient than the flood algorithm,and the search algorithm is improved on the basis of the number of search steps and the search time.